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Meet up

Cloud Native September

Wednesday, 4th September at CodeNode, London

This meetup was organised by Cloud Native LDN in September 2019

Welcome Autumn with Cloud Native as we discuss using Machine Learning to automate pipelines, using a globally distributed cloud platform and more!

Utilising OSS to Operate a Centralised, Globally Distributed Cloud Platform

Condé Nast International is home to some of the largest online publications in the world - including Vogue, GQ, Wired, and Vanity Fair. In an effort to provide a cohesive vision for these brands across more than 30 markets, a truly global platform was required. Utilising AWS and Kubernetes at its core, the platform officially launched in September 2018 and serves over 200 million unique visitors/month. Of course, operating Cloud Native Infrastructure is more than just spinning up a container orchestrator! Auxiliary services are required in order to operate it effectively and provide developers with a true platform experience. Open Source Software (OSS) forms the backbone for much of what we do. As such, this talk will be focusing on how Condé Nast International utilises OSS to effectively operate multiple Kubernetes clusters across the world, paying special attention to observability, testing, application delivery, and developer experience.

Josh Michielsen

Josh Michielsen is a Senior Software Engineer for the Platform Engineering team at Condé Nast International, where he helps to drive the vision of a truly global platform to house some of the worlds largest online publications! He specialises in container orchestration, software development, continuous delivery, and cloud operations. When he's not wrangling with Kubernetes or checking if err != nil in Go, he is a hobbyist data scientist, photographer, cyclist, and doge owner living in Cambridge, UK.

Automating Deployment Pipelines with Machine Learning

Imagine if you could apply machine learning to real developer use cases? This talk will detail 7 unsupervised machine learning algorithms and how they can be applied to a deployment pipeline so that developers can automate the QA, testing, and deployment verification of code.

Three Takeaways:

QA, Testing and deployment verification remains a manual task for dev/ops teams, several hours are added to a typical deployment pipeline (dev > prod)

Metrics, Telemetry, and application events are readily available from run-time, logs, and tools, but are fragmented and require human interpretation

Machine Learning and NLP algorithms can be used to automate QA/testing/verification (the interpretation of time-series metrics and unstructured data)

Automating Deployment Pipelines with Machine Learning

Imagine if you could apply machine learning to real developer use cases? This talk will detail 7 unsupervised machine learning algorithms and how they can be applied to a deployment pipeline so that developers can automate the QA, testing, and deployment verification of code.

Steve Burton

Steve is the VP of marketing at Harness and has also worked at Moonsoft and Glassdoor. He specialises in Disruptive Marketing, Application Performance Management, SaaS, Freemium & Enterprise Software.

Cloud Native Telegraf

Telegraf is an agent for collecting, processing, aggregating, and writing metrics. With over 200 plugins, Telegraf can fetch metrics from a variety of sources, allowing you to build aggregations and write those metrics to InfluxDB, Prometheus, Kafka, and more. In this talk, we will take a look at some of the lesser known, but awesome, plugins that are often overlooked; that allow Telegraf to monitor your cloud native applications.

David McKay

David McKay is a software and technology professional, born & bred in Glassgow, Scotland. As a serial user-group organiser, founding Cloud Native, Docker, DevOps, mongoDB, and Pair Programming Glassgow; David is always searching for new and creative ways to share knowledge with others.

Thanks to our sponsors

Attending Members

Overview

Welcome Autumn with Cloud Native as we discuss using Machine Learning to automate pipelines, using a globally distributed cloud platform and more!

Utilising OSS to Operate a Centralised, Globally Distributed Cloud Platform

Condé Nast International is home to some of the largest online publications in the world - including Vogue, GQ, Wired, and Vanity Fair. In an effort to provide a cohesive vision for these brands across more than 30 markets, a truly global platform was required. Utilising AWS and Kubernetes at its core, the platform officially launched in September 2018 and serves over 200 million unique visitors/month. Of course, operating Cloud Native Infrastructure is more than just spinning up a container orchestrator! Auxiliary services are required in order to operate it effectively and provide developers with a true platform experience. Open Source Software (OSS) forms the backbone for much of what we do. As such, this talk will be focusing on how Condé Nast International utilises OSS to effectively operate multiple Kubernetes clusters across the world, paying special attention to observability, testing, application delivery, and developer experience.

Josh Michielsen

Josh Michielsen is a Senior Software Engineer for the Platform Engineering team at Condé Nast International, where he helps to drive the vision of a truly global platform to house some of the worlds largest online publications! He specialises in container orchestration, software development, continuous delivery, and cloud operations. When he's not wrangling with Kubernetes or checking if err != nil in Go, he is a hobbyist data scientist, photographer, cyclist, and doge owner living in Cambridge, UK.

Automating Deployment Pipelines with Machine Learning

Imagine if you could apply machine learning to real developer use cases? This talk will detail 7 unsupervised machine learning algorithms and how they can be applied to a deployment pipeline so that developers can automate the QA, testing, and deployment verification of code.

Three Takeaways:

QA, Testing and deployment verification remains a manual task for dev/ops teams, several hours are added to a typical deployment pipeline (dev > prod)

Metrics, Telemetry, and application events are readily available from run-time, logs, and tools, but are fragmented and require human interpretation

Machine Learning and NLP algorithms can be used to automate QA/testing/verification (the interpretation of time-series metrics and unstructured data)

Automating Deployment Pipelines with Machine Learning

Imagine if you could apply machine learning to real developer use cases? This talk will detail 7 unsupervised machine learning algorithms and how they can be applied to a deployment pipeline so that developers can automate the QA, testing, and deployment verification of code.

Steve Burton

Steve is the VP of marketing at Harness and has also worked at Moonsoft and Glassdoor. He specialises in Disruptive Marketing, Application Performance Management, SaaS, Freemium & Enterprise Software.

Cloud Native Telegraf

Telegraf is an agent for collecting, processing, aggregating, and writing metrics. With over 200 plugins, Telegraf can fetch metrics from a variety of sources, allowing you to build aggregations and write those metrics to InfluxDB, Prometheus, Kafka, and more. In this talk, we will take a look at some of the lesser known, but awesome, plugins that are often overlooked; that allow Telegraf to monitor your cloud native applications.

David McKay

David McKay is a software and technology professional, born & bred in Glassgow, Scotland. As a serial user-group organiser, founding Cloud Native, Docker, DevOps, mongoDB, and Pair Programming Glassgow; David is always searching for new and creative ways to share knowledge with others.

Thanks to our sponsors

Who's coming?

Attending Members